class_docstr: The class wrapper the PGL graph, the class involve the funtions to implement struc2vec algorithm.
docstr: According to struct distance to walk the path 
docstr_tok: ["According","to","struct","distance","to","walk","the","path"]
code: def random_walk_structual_sim(self):
      """
      According to struct distance to walk the path
      """
      from pathos.multiprocessing import Pool
  
      print("start process struc2vec random walk.")
      walks_process_ids = [i for i in range(0, self.num_walks)]
      pool = Pool(10)
      walks = pool.map(self.executor_random_walk, walks_process_ids)
      pool.close()
      pool.join()
  
      # save the final walk result
      file_result = open(args.tag + "_walk_path", "w")
      for walk in walks:
          for walk_node in walk:
              walk_node_str = " ".join(
                  [str(node) for node in walk_node]
              )
              file_result.write(walk_node_str + "\n")
      file_result.close()
      print("process struc2vec random walk done.")
  
imports: import argparse
  import math
  import random
  import numpy
  import pgl
  from pgl import graph
  from pgl.graph_kernel import alias_sample_build_table
  from pgl.sample import alias_sample
  from data_loader import EdgeDataset
  from classify import train_lr_model
  from sklearn_classify import train_lr_l2_model
label_desc: Use image node_id 14 for calling the StrucVecGraph obj's underlying member method code with example usage: obj.random_walk_structual_sim() without return types